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A zero phase adaptive fuzzy Kalman filter for physiological tremor suppression in robotically assisted minimally invasive surgery

Hongqiang Sang, Chenghao Yang, Fen Liu, Jintian Yun, Guoguang Jin, Fa Chen

Year
2016
Citations
16

Abstract

BACKGROUND: Hand physiological tremor of surgeons can cause vibration at the surgical instrument tip, which may make it difficult for the surgeon to perform fine manipulations of tissue, needles, and sutures. METHODS: A zero phase adaptive fuzzy Kalman filter (ZPAFKF) is proposed to suppress hand tremor and vibration of a robotic surgical system. The involuntary motion can be reduced by adding a compensating signal that has the same magnitude and frequency but opposite phase with the tremor signal. RESULTS: Simulations and experiments using different filters were performed. Results show that the proposed filter can avoid the loss of useful motion information and time delay, and better suppress minor and varying tremor. CONCLUSIONS: The ZPAFKF can provide less error, preferred accuracy, better tremor estimation, and more desirable compensation performance, to suppress hand tremor and decrease vibration at the surgical instrument tip. Copyright © 2016 John Wiley & Sons, Ltd.

Keywords

Kalman filterComputer scienceSIGNAL (programming language)Compensation (psychology)Control theory (sociology)Adaptive filterVibrationFilter (signal processing)Artificial intelligenceComputer vision

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